Optimizing data retrieval from an active implantable medical device

ABSTRACT

An external data retrieval apparatus includes a transceiver, and a processing system coupled to the transceiver. The processing system obtains a plurality of measures over a period of time. The measures relate to a quality of a communications channel between the data retrieval apparatus and an active implantable medical device. The processing system determines a trend in the plurality of measures over the period of time, and then determines a preferred time during which to retrieve data based on the trend.

BACKGROUND

1. Field

The present disclosure relates generally to wireless communicationsinvolving active implantable medical devices, and more particularly, toapparatuses and methods for optimizing the retrieval of data from activeimplantable medical devices.

2. Background

Modern active implantable medical devices, such as neurostimulators,pacemakers, and ICDs, are capable of not only monitoring patientcondition and delivering therapy, but are capable of storing detaileddata and diagnostics relating to a patient's condition for laterretrieval. Analysis of this data can improve patient care dramatically,and allow fine-tuning the performance of the implantable devices byprogramming them with new operational parameters. Interrogation of animplantable medical device allows data stored in the device to beretrieved by an external device. After analysis, reprogramming thedevice allows its performance to be optimized based on the interrogateddata.

An active implantable medical device can store data, for laterretrieval, that are useful for assessment of the patient's medicalstatus and for determining the operational status of the implantablemedical device. Retrieval of such data, however, requires establishmentof communications links between the implantable medical device and anexternal device. Such communications may consume significant implantablemedical device energy, which may reduce the longevity of the implantablemedical device. Furthermore, an implantable medical device has limitedmemory for storing patient data. As such, infrequent retrieval of patentdata from an implantable medical device may cause the implantablemedical device to stop storing data, or to overwrite older data in orderto store new data.

It would be desirable to provide mechanisms that optimize the retrievalof patient data in a manner that reduces implantable medical deviceenergy consumption and prevents loss of stored patient data. Theconcepts disclosed below address these needs and others.

SUMMARY

In one aspect of the disclosure, a method of, and apparatus for, dataretrieval by an external data retrieval apparatus are provided. Themethod involves obtaining a number of measures over a period of time.The measures correspond to a quality of a communications channel betweenthe data retrieval apparatus and an active implantable medical device.The method also includes determining a trend in the number of measuresover the period of time. The trends may represent changes in themeasures as a function of time. The further includes determining apreferred time during which to retrieve data based on the trend. Forexample, the time may be the time in the trend at which the qualitymeasure is at a peak, or a time range during which the quality measureexceeds a minimum quality threshold. The apparatus includes atransceiver and a processing system. The processing system is coupled tothe transceiver and includes various modules configured to perform thedescribed method.

Thus, in this aspect of the disclosure, a data retrieval apparatusqueries an active implantable medical device systematically to assessthe time periods when the signal strength at the data retrievalapparatus is maximal for extended periods of time. The method involvesperiodic, brief communications between the data retrieval apparatus andthe active implantable medical device to determine when the activeimplantable medical device is in close proximity to the data retrievalapparatus. Further optimizations determine the central periods of timewhen the active implantable medical device is most likely to be in closeproximity to maximize the probability of energy transfer using the leastactive implantable medical device battery energy possible.

In another aspect of the disclosure, a method of, and apparatus for,power transmission control by an active implantable medical device areprovided. The method involves receiving a measure of quality of a signaltransmitted by the active implantable medical device. The measure isreceived from an external data retrieval apparatus that received thesignal transmitted by the active implantable medical device. The methodalso includes comparing the measure to a criterion. The criterion maycorrespond to a minimum quality measure, which in turn, corresponds to aminimum performance requirement, e.g., data rate, for a communicationchannel between the active implantable medical device and the dataretrieval apparatus. The measure of quality may be one of asignal-to-noise ratio, a received signal strength indicator, or a packeterror rate. The method further involves adjusting a signal transmissionpower level of the active implantable medical device until the measureis at or near the criterion. The apparatus includes a transceiver and aprocessing system. The processing system is coupled to the transceiverand includes various modules configured to perform the described method.

Thus, in this aspect of the disclosure, an active implantable medicaldevice uses a feedback signal from a data retrieval apparatus to adjustthe level of RF transmission power by the active implantable medicaldevice to produce the minimum signal strength at the data retrievalapparatus needed to reliably support quality communication between theactive implantable medical device and the data retrieval apparatus.

In another aspect of the disclosure, a method of, and apparatus for,data retrieval by an external data retrieval apparatus are provided. Themethod involves retrieving different data types from active implantablemedical device, where each data type has a portion of a memory of theactive implantable medical device allocated thereto. The method alsoinvolves, for each of the different data types, scheduling a nextretrieval of the data type based on a known period of time or based ontime data included in retrieved data. The data type may be a first typethat corresponds to a count of a number of occurrences of at least onetype of a physiological event over a period of time. In this case, thetime until the next scheduled retrieval of the first type is apercentage of the period of time. The data type may be a second typethat corresponds to a time of occurrence of each of a plurality ofphysiological events, in order of occurrence. In this case, the timeuntil the next scheduled retrieval of the second type is a percentage ofelapsed time between the oldest occurrence and the most recentoccurrence. The data type may be a third type that corresponds to one ormore waveforms of one or more physiological events. In this case, thetime until the next scheduled retrieval of the third type is apercentage of the time elapsed since the occurrence of the oldestwaveform. The method may also include setting a limit on the amount ofdata to be retrieved during a period of time. In this case, the dataretrieval schedule thus described is subordinate to the limit. Theapparatus includes a transceiver and a processing system. The processingsystem is coupled to the transceiver and includes various modulesconfigured to perform the described method.

Thus, in this aspect of the disclosure, adaptive interrogation intervalsare implemented by a data retrieval apparatus. The adaptation recognizesseveral data types present in an active implantable medical device thathave differing time intervals prior to overwrite. The disclosed methodassesses when retrieval should occur on a differential basis based onthe data type so that data overwrite does not occur for any data type,while avoiding too frequent data transfer for any data type that couldincrease energy usage by the active implantable medical device. Theadaptation also accounts for incorporation of programmable constraintsthat limit total data retrieval to avoid active implantable medicaldevice battery depletion. Such constraints may be on a per-time basis oron a total data per time basis.

It is understood that other aspects of apparatuses and methods willbecome readily apparent to those skilled in the art from the followingdetailed description, wherein various aspects of apparatuses and methodsare shown and described by way of illustration. As will be realized,these aspects may be implemented in other and different forms and itsseveral details are capable of modification in various other respects.Accordingly, the drawings and detailed description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of apparatuses and methods will now be presented in thedetailed description by way of example, and not by way of limitation,with reference to the accompanying drawings, wherein:

FIG. 1 is a schematic illustration of a patient's head showing theplacement of an implantable medical device;

FIG. 2 is a block diagram of a system for providing communicationbetween local medical devices and remote system components;

FIG. 3 is a block diagram of an implantable medical device;

FIG. 4 is a block diagram of a data retrieval apparatus;

FIG. 5 is a diagram of a patient with an implantable medical devicelocated near a data retrieval apparatus;

FIG. 6 is graph illustrating a communication quality measurement as afunction of communication performance;

FIG. 7 is a diagram of data types and memory allocation in animplantable medical device;

FIG. 8A are illustrations of physiological waveforms detected by animplantable medical device;

FIG. 8B are illustrations of histogram data collected by an implantablemedical device;

FIG. 8C are illustrations of detailed physiological waveforms recordedby an implantable medical device;

FIG. 9 is a timeline illustrating three different data types recorded byan implantable medical device;

FIG. 10 is a schematic diagram illustrating various location of apatient relative to a data retrieval apparatus;

FIG. 11 is a graph illustrating a communication quality measurement foreach of the patient location positions of FIG. 10;

FIG. 12 is a graph illustrating various communication qualitymeasurements as a function of time of day;

FIG. 13 is an illustration of a table of individual and averagecommunication quality measurements over a seven day period.

FIG. 14 is a graph illustrating a curve fitted to communication qualitymeasurements spanning a 24 hour period;

FIG. 15 is the graph of FIG. 14 further identifying a time of a peakcommunication quality measurement;

FIG. 16 is the graph of FIG. 14 further identifying a time range duringwhich communication quality measurements satisfy a threshold;

FIG. 17 is a flow chart of a method of retrieving patient data from animplantable medical device;

FIG. 18 is the graph of FIG. 6 further identifying periods correspondingto different rates of change in a communication quality measurement as afunction of communication performance;

FIG. 19 is a flow chart of a method of adjusting power transmission ofan implantable medical device;

FIG. 20 is the timeline of FIG. 9 further identifying times at whichdifferent data types recorded by an implantable medical device areretrieved by a data retrieval apparatus;

FIG. 21 is a flow chart of a method of scheduling data retrieval by adata retrieval apparatus;

FIG. 22 is a diagram of an exemplary hardware implementation of a dataretrieval apparatus; and

FIG. 23 is a diagram of an exemplary hardware implementation of animplantable medical device.

DETAILED DESCRIPTION

Various aspects of the disclosure will be described more fullyhereinafter with reference to the accompanying drawings. This disclosuremay, however, be embodied in many different forms by those skilled inthe art and should not be construed as limited to any specific structureor function presented herein. Rather, these aspects are provided so thatthis disclosure will be thorough and complete, and will fully convey thescope of the disclosure to those skilled in the art. Based on theteachings herein, one skilled in the art should appreciate that thescope of the disclosure is intended to cover any aspect of thisdisclosure, whether implemented independently of or combined with anyother aspect of the disclosure. For example, an apparatus may beimplemented or a method may be practiced using any number of the aspectsset forth herein. In addition, the scope of the disclosure is intendedto cover such an apparatus or method which is practiced using otherstructure and/or functionality in addition to or instead of otheraspects of this disclosure. It should be understood that any aspect ofthe disclosure disclosed herein may be embodied by one or more elementsof a claim.

The concepts disclosed may be implemented in hardware or software thatis executed on a hardware platform. The hardware or hardware platformmay be a general purpose processor, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA) or other programmable logic component, discrete gateor transistor logic, discrete hardware components, or any combinationthereof, or any other suitable component designed to perform thefunctions described herein. A general-purpose processor may be amicroprocessor, but in the alternative, the processor may be anyconventional processor, controller, microcontroller, or state machine. Aprocessor may also be implemented as a combination of computingcomponents, e.g., a combination of a DSP and a microprocessor, aplurality of microprocessors, one or more microprocessors in conjunctionwith a DSP, or any other such configuration.

Software shall be construed broadly to mean instructions, instructionsets, code, code segments, program code, programs, subprograms, softwaremodules, applications, software applications, software packages,routines, subroutines, objects, executables, threads of execution,procedures, functions, etc., whether referred to as software, firmware,middleware, microcode, hardware description language, or otherwise. Thesoftware may reside on a computer-readable medium. A computer-readablemedium may include, by way of example, a magnetic storage device (e.g.,hard disk, floppy disk, magnetic strip), an optical disk (e.g., compactdisk (CD), digital versatile disk (DVD)), a smart card, a flash memorydevice (e.g., card, stick, key drive), random access memory (RAM), readonly memory (ROM), programmable ROM (PROM), erasable PROM (EPROM),electrically erasable PROM (EEPROM), a general register, or any othersuitable non-transitory medium for storing software.

As mention above, an implantable medical device (IMD) such as apacemaker, implantable defibrillator, or neurostimulator stores datathat are useful for assessing patient medical status and for determiningthe operational status of the implantable medical device. However, theamount of memory present in the implantable medical device is limited,so eventually the implantable medical device may stop storing data, ormay need to overwrite older data to store new data. The term “overwrite”is used herein to describe data loss resulting from limited memory. Toavoid overwrite, it is desirable to have a home appliance that canretrieve data from the implantable medical device between office visitsin the patient's home. Such a home appliance, hereafter referred to as adata retrieval apparatus (DRA), would ideally use radio frequency (RF)telemetry to retrieve data transcutaneously from the implantable medicaldevice when the patient is in close proximity. The data retrievalapparatus could be a standalone device that the patient would bring totheir physician for read-out, or it could be internet connected to acentral database. Ideally the data retrieval apparatus would have atelemetry range long enough for it to be placed in a convenient locationwhere it could establish the telemetry link on a periodic basis withoutpatient intervention. The methods and apparatuses described herein (1)automate the setup process of the data retrieval apparatus for both thepatient and physician, (2) avoid data overwrite, and (3) minimize theenergy consumed by the implantable medical device when transmitting datato the data retrieval apparatus. Automation of the setup process reducesphysician workload. Avoiding data overwrite improves patient assessmentand care. Reducing energy consumed by the implantable medical deviceduring data transmission increases the life of the implantable medicaldevice's battery and reduces the frequency of implantable medical devicereplacement surgical procedures, which in turn lowers surgicalcomplications and reduces total medical costs.

With reference to FIG. 1, an exemplary implantable medical device 102 isshown implanted in a patient 104. In one configuration, the implantablemedical device 102 includes a small self-contained brainwave detectingdevice. As the term is used herein, a brainwave detecting or recordingdevice is a device capable of detecting or predicting ictal activity (orother neurological events) for providing data useful in the diagnosis ofa neurological disorder. Further, the term recording device, as usedherein, is a device that can either record neurological signals, such asEEG signals, or detect and analyze EEG signals and create a log of suchan analysis.

The implantable medical device 102 may be configured to detect orpredict neurological events that have a representative electrographicsignature. For example, the implantable medical device 102 may beresponsive to epileptic seizures. It should, however, be recognized thatit is also possible to respond to other types of neurological disorders,such as movement disorders (e.g. the tremors characterizing Parkinson'sdisease), migraine headaches, chronic pain, and neuropsychiatricdisorders such as depression.

With reference to FIG. 2, an exemplary patient monitoring system 200 isillustrated. The patient monitoring system 200 includes local componentsand remote components that communicate through a communications network202, such as the Internet. Local components are located in the vicinityof the patient, such as the patient's residence, and may include animplantable medical device 204, and a local device 206, referred toherein as a data retrieval apparatus. Remote components are located asignificant distance from the patient, such as at a hospital or careprovider's office. Remote components may include, for example, aprogrammer 208, a network server 210 and a database 212.

The programmer 208 is typically operated by medical personnel (such asthe patient's treating physician) to control the operation of theimplantable medical device 204. In general terms, the programmer 208functions as a clinical interface to the implantable medical device 204,allowing the implantable medical device parameters to be modified, andfor data and/or program code to be uploaded from and downloaded to theimplantable medical device.

The database 212 serves as a centralized data repository for all datarelevant to the operation of the system 200, and may include clinicaldata, program code, and more. The network server 210 acts as the primaryinterface between the database 212 and other devices attached to thecommunications network 202. Although it might be possible andadvantageous in certain circumstances to communicate directly with thedatabase 212, it is generally preferable to configure the network server210 to receive queries, perform necessary authentication, access thedatabase 212, and respond as necessary, thereby reducing the processingload on the database and also reducing the exposure of the database tonetwork traffic (thereby improving security).

The data retrieval apparatus 206 is configured to receive data fromremote components through the communications network 202 and provide itto the implantable medical device 204. Such data may include, forexample, program code or instructions from a programmer 208 that affectthe operation of the implantable medical device 204. The data retrievalapparatus 206 is also configured to retrieve data from the implantablemedical device 204 and to forward it to one or more of the remotecomponents. As described further below, communication between the dataretrieval apparatus 202 and the implantable medical device 204 iswireless, and may be in the form of short-range telemetry by inductivecoupling or long-range telemetry by RF communications.

An overall block diagram of an implantable medical device 304 used formeasurement, detection, and treatment is illustrated in FIG. 3. Insidethe housing of the device 304 are several subsystems making up a controlmodule 310. The control module 310 is capable of being coupled to aplurality of electrodes 312, 314, 316, and 318 for sensing andstimulation. Although four electrodes are shown in FIG. 3, it should berecognized that any number is possible.

The electrodes 312-318 are connected to an electrode interface 320.Preferably, the electrode interface is capable of selecting eachelectrode as required for sensing and stimulation; accordingly theelectrode interface is coupled to a detection subsystem 322 and astimulation subsystem 324. The electrode interface also may provide anyother features, capabilities, or aspects, including but not limited toamplification, isolation, and charge-balancing functions, that arerequired for a proper interface with neurological tissue and notprovided by any other subsystem of the implantable medical device 304.

The detection subsystem 322 includes an EEG analyzer function. The EEGanalyzer function is adapted to receive EEG signals from the electrodes312-318, through the electrode interface 320, and to process those EEGsignals to identify neurological activity indicative of a seizure, anonset of a seizure, or a precursor to a seizure. One way to implementsuch EEG analysis functionality is disclosed in detail in U.S. Pat. No.6,016,449 to Fischell et al., which is hereby incorporated by reference.The detection subsystem may optionally also contain further sensing anddetection capabilities, including but not limited to parameters derivedfrom other physiological conditions (such as electrophysiologicalparameters, temperature, blood pressure, etc.).

The stimulation subsystem 324 is capable of applying electricalstimulation to neurological tissue through the electrodes 312-318. Thiscan be accomplished in any of a number of different manners. Forexample, it may be advantageous in some circumstances to providestimulation in the form of a substantially continuous stream of pulses,or on a scheduled basis. Preferably, therapeutic stimulation is providedin response to abnormal events detected by the EEG analyzer function ofthe detection subsystem 322. As illustrated in FIG. 3, the stimulationsubsystem 324 and the EEG analyzer function of the detection subsystem322 are in communication; this facilitates the ability of stimulationsubsystem 324 to provide responsive stimulation as well as an ability ofthe detection subsystem 322 to blank the amplifiers while stimulation isbeing performed to minimize stimulation artifacts. It is contemplatedthat the parameters of the stimulation signal (e.g., frequency,duration, waveform) provided by the stimulation subsystem 324 would bespecified by other subsystems in the control module 310.

Also in the control module 310 is a memory subsystem 326 and a centralprocessing unit (CPU) 328, which can take the form of a microcontroller.The memory subsystem 326 is coupled to the detection subsystem 322(e.g., for receiving and storing data representative of sensed EEGsignals and evoked responses), the stimulation subsystem 324 (e.g., forproviding stimulation waveform parameters to the stimulation subsystem),and the CPU 328, which can control the operation of the memory subsystem326. In addition to the memory subsystem 326, the CPU 328 is alsoconnected to the detection subsystem 322 and the stimulation subsystem324 for direct control of those subsystems.

The memory subsystem 326 may include one or more types of memory,including for example, random access memory (RAM), read only memory(ROM), and non-volatile memory (NVM). As explained further below, withinone or more of the types of memory, such as RAM, there may be sectionsof memory reserved for the following: 1) EEG waveform data (storedECoG's), 2) detailed event data regarding detection activity, 3)long-term histogram data on detections, and 4) device diagnosticinformation (battery voltage, lead impedance, radio usage, etc)

Also provided in the control module 310, and coupled to the memorysubsystem 326 and the CPU 328, is a communication subsystem 330. Thecommunication subsystem 330 enables communication between theimplantable medical device 204 (FIG. 2) and the outside world, e.g., thedata retrieval apparatus 206 (FIG. 2). The communication subsystem 330may include a telemetry coil (which may be situated outside of thehousing) enabling short-range transmission and reception of signals, toor from the implantable medical device 204, via inductive coupling. Thecommunication subsystem 330 may also include a transceiver and one ormore antennas for long-range telemetry by an RF communications link withthe implantable medical device 204.

Rounding out the subsystems in the control module 310 are a power supply332 and a clock supply 334. The power supply 332 supplies the voltagesand currents necessary for each of the other subsystems. The clocksupply 334 supplies substantially all of the other subsystems with anyclock and timing signals necessary for their operation.

While the memory subsystem 326 is illustrated in FIG. 3 as a separatefunctional subsystem, the other subsystems may also require variousamounts of memory to perform the functions described above and others.Furthermore, while the control module 310 is preferably a singlephysical unit contained within a single physical enclosure, namely thehousing, it may comprise a plurality of spatially separate units eachperforming a subset of the capabilities described above. Also, thevarious functions and capabilities of the subsystems described above maybe performed by electronic hardware, computer software (or firmware), ora combination thereof.

Referring now to FIG. 4, a block diagram representing a data retrievalapparatus 406 is set forth in detail. The data retrieval apparatus 406includes a general-purpose or special-purpose computer programmed oradapted for use as described herein. The data retrieval apparatus 406includes a wide area communications interface 412 for communicationswith the communications network 202 (FIG. 2), and a local areacommunications interface 414 for communications with the implantablemedical device 204. The wide area communications interface 412 may be,for example, an Internet connection. The local area communicationsinterface 414 may be an inductive short-range telemetry system includingan inductive coil, or a long-range RF telemetry system including an RFantenna. The method and apparatuses disclosed herein are primarilydirected to RF telemetry communications. Preferably, both the wide areacommunications interface 412 and the local area communications interface414 are capable of bi-directional communications.

The data retrieval apparatus 406 is controlled by a CPU 416. The CPU iscoupled, either directly or through a bus controller, to the wide areacommunications interface 412, the local area communications interface414, a memory subsystem 418 for programming and short-term storage, astorage subsystem 420 (which might include a hard drive, flash memory,and other non-volatile storage), and an input/output subsystem 422 usedto pass information to and receive information from a user. The memorysubsystem 418 may include ROM, dynamic RAM, and other random-accessmemory. The storage subsystem 420 may include a hard drive, flashmemory, and other non-volatile storage.

The operation of the data retrieval apparatus 406 is controlled by apower supply 424 and a clock supply 426. The power supply 424 typicallyincludes batteries. Alternatively, the data retrieval apparatus 406 mayreceive power from an AC outlet. A combination of the two sources mightalso be used. The clock supply 426 supplies substantially all of theother subsystems of the network unit with any clock and timing signalsnecessary for their operation.

As with the implantable medical device 304 (FIG. 3) described above,while the memory subsystem 418 is illustrated in FIG. 4 as a separatefunctional subsystem, the other subsystems may also require variousamounts of memory to perform the functions described herein and others.Furthermore, while the data retrieval apparatus 406 is preferably asingle physical unit contained within a single physical enclosure,namely the housing, it may comprise a plurality of spatially separateunits each performing a subset of the capabilities described herein.

The various functions and capabilities of the subsystems of the dataretrieval apparatus 406 described above may be performed by electronichardware, computer software, or firmware, or a combination thereof. Theillustration of FIG. 4 shows several of the major functional subsystemspresent in a data retrieval apparatus consistent with the invention.However, in many computing systems, other functional subsystems andmodules are present that are not necessarily reflected in FIG. 4.Moreover, a data retrieval apparatus 406 may integrate two or more ofthe above-referenced subsystems. For example, the wide areacommunications interface 412 and the local area communications interface414 might be adapted into a single subsystem if efficiencies resultthere from. Accordingly, FIG. 4 is for purposes of illustration only,and does not necessarily reflect the actual configuration of the dataretrieval apparatus. It is, however, considered to be representative.

For a battery powered implantable medical device, minimizing powerconsumption during RF data transmission is very important because theimplanted power source has a limited useful life (even in the case of animplantable medical device with a rechargeable battery). The geometricalconsiderations relative to an implantable medical device communicatingvia wireless telemetry are shown in FIG. 5. A patient 502 is shown withan implantable medical device 504 that has an approximately isotropicantenna capable of establishing a wireless telemetry link with a dataretrieval apparatus 506. The data retrieval apparatus 506 that islocated a separation distance D from the patient 502. An approximatelyisotropic antenna is desired to insure that the implantable medicaldevice 504 could reliably establish a connection with the data retrievalapparatus 506 regardless of the orientation of the patient with respectto the data retrieval apparatus. Because an implantable medical device504 is constrained in size and therefore has a relatively small antennasize (e.g., 1-10 cm) compared to the separation distance D (e.g., 1-5m), the RF electric field strength produced at the data retrievalapparatus 506 by the implantable medical device 504 for a giventransmission power will follow an approximately 1/R² drop off and willcorrelate with the signal-to-noise ratio (SNR) measured at the dataretrieval apparatus 506 for a given noise environment.

Direct measurement of signal-to-noise is not always practical, so oftenalternative methods may be used to assess signal strength. Onealternative method of signal strength is referred to as the receivedsignal strength indication (RSSI). The received signal strengthindication metric describes the power present in a received radio signaltypically in arbitrary units that can be reported as a DC voltage or asa digital value (e.g., 0 to 255 levels). The received signal strengthindication correlates with the signal-to-noise for a given noiseenvironment with higher received signal strength indication correlatingwith higher signal-to-noise.

Another alternative method of assessing signal strength is to measurethe number of communication retries or correctable errors encounteredduring data transfer. Most digital communication protocols have a lowlevel means of assessing whether a small portion of data (typicallycalled a packet) of the total data digital transmission was communicatedcorrectly. Two such methods are use of a parity bit or a cyclicredundancy check (CRC). These methods are well known to those skilled inthe art and are not described in detail here. Essentially each methodinvolves the inclusion of small amount of additional data (parity bit orcheck value) that mathematically describes the actual data being sent.As packet data are received, the test data are compared to the actualdata per the defined relationship on a packet by packet basis to detecterrors in the transmitted data. If an error is detected, retransmissionof the packet is triggered. More advanced systems includeerror-correction codes which allow recovery of a packet of data with asmall number of errors. However, if the number of errors exceeds thenumber of correctable errors, then the errors are considered“uncorrectable” and the entire packet of data is retransmitted. Byassessing a series of data packet transmissions, the packet error rate(PER) can be determined by dividing the number of incorrectlytransmitted packets by the total number of transmitted packets. Thepacket error rate will inversely correlate with the signal-to-noise withlower packet error rate correlating with higher signal-to-noise.

In the descriptions that follow the term signal-to-noise is generallyused as the metric to describe the signal level, however, it should beunderstood that alternative methods of signal strength measurement suchas received signal strength indication or packet error rate could beused as the signal strength metric for the methods described herein.Furthermore, because this disclosure does not address methods of signalstrength assessment, but rather methods of optimizing data transferusing signal strength metrics, other methods of measuring signalstrength not described herein could be used for the implementation ofthe techniques disclosed herein as well and use of such alternativeswould not alter materially such techniques.

Referring to FIG. 5 again, at a distance of 1 m, the signal-to-noise maybe X, but at 2 m the signal-to-noise will be reduced to X/4, and at 3 mthe signal-to-noise will be reduced to X/9. Thus increasing the distanceD reduces the signal-to-noise measured at the data retrieval apparatus,and eventually the signal-to-noise becomes too low and communicationerrors may result. The RF transmission power of the implantable medicaldevice 504 may be increased to correspondingly increase thesignal-to-noise, but such increased transmission power comes at theexpense of more rapidly depleting the implantable medical device 504battery.

Another option is to slow the data rate. Shannon's Channel CapacityTheorem, defines the maximum rate C of reliable (error-free) informationtransmission through a digital communications channel with bandwidth Bas a function of the signal-to-noise as follows:C=B×log₂(1+signal-to-noise)bits/sec  (Eq. 1)

The relationship is plotted in FIG. 6 normalized per Hz of bandwidth. Asthe signal-to-noise is decreased, the data rate for reliablecommunications decreases with the greatest rate of change occurring atlower signal-to-noise values. As a result, at greater separationdistances D, the data rate from the implantable medical device 504 tothe data retrieval apparatus 506 could be reduced to allowcommunications at the lower signal-to-noise; however, it would then takelonger to transmit the data, which also results in additional energyconsumption.

Based on the above considerations, data retrieval ideally should beperformed at a time when the distance D is minimized for a sufficientperiod of time for data retrieval to occur, which could take severalminutes, to minimize the implantable medical device 504 battery energyused.

Another consideration for data retrieval is determining when dataretrieval is required to avoid data loss. It is likely that animplantable medical device 504 is configured to store different types ofdata. This concept is illustrated in FIG. 7 where the implantablemedical device memory 702 is shown subdivided into sections, with adifferent type of data allocated to each section. The sections shownhere are for illustrative purposes and a specific implantable medicaldevice may have additional or different sections.

An implantable medical device can be configured to store different typesof data in different sections of memory as shown in FIG. 7 whendifferent events occur. For example, an implantable medical device 204may be configured to detect a specific pattern present in a biologicalwaveform. If this pattern occurs it may result in data storage in onesection of memory, but not in another section of memory. Alternativelyit could result in storage in multiple sections of memory in differentforms as will be described. These sections of memory are associated withspecific data types and are referred to in association with the type ofdata (e.g., histogram data memory), however, all types of data memoryrefer to sections of the memory subsystem 326 (FIG. 3), which mayinclude one or more of RAM and non-volatile memory.

With reference to FIG. 7, histogram data memory 704 is used for countingthe number of events for which it is configured to store informationwithin a series of fixed time windows that extend over a multiple ofsuch time windows. For example, an implantable medical device may countfour different types of events on an hourly basis for the past 10 days.In this case, the implantable medical device has 4 bins for every hourfor 10 days (4 bins×24 hours×10 days) and would likely not overwritehistogram data memory 704 prior to 10 days elapsing since the data waslast transferred.

With continued reference to FIG. 7, detailed event sequence data memory706 is used to store highly time accurate (e.g., to the second)information about physiological events. The data stored in this memorydiffers from the histogram data stored in the histogram data memory 704in that it records the type and order of occurrence of events along withthe exact time of occurrence. For example, if two “A type”, one “B type”and one “C type” events occurred within a given hour, and the histogramdata memory 704 was configured to store information for A and B events,and the event sequence data memory 706 was configured to storeinformation on A, B and C type events, these different types of memoriesmight record the following:

Detailed event sequence Histogram data memory 704 data memory 706 A = 2,B = 1 (from 1:00-2:00) A occurred at 1:23:21 B occurred at 1:25:33 Coccurred at 1:38:44 A occurred at 1:55:12

Hence, the detailed event sequence data memory 706 captures the orderand timing of the events, whereas the histogram data memory onlycaptures the total count of events within regularly spaced elapsed timeintervals. As a result, a fixed amount of detailed event sequence datamemory 706 fills at different rates depending on the rate of eventoccurrence. For example, the detailed event sequence data memory 706 mayfill at a faster rate when events are happening at a faster rate.Accordingly, the elapsed time until overwrite of this data type varies.

The final type of memory in FIG. 7 is waveform data memory 708. Thistype of memory is generally used for storage based on the occurrence ofspecific events, referred to herein as “waveform data events.” Waveformdata events may or may not trigger storage in the other two types ofaforementioned memory. Waveform data memory 708 is generally configuredto store several separate waveform data events. The waveform data memory708 used to record these waveform data events is generally configured torecord a plurality of events in sequence. For example, the implantablemedical device may be configured to store three such waveform dataevents, and in this case overwrite occurs after the fourth waveform dataevent occurred.

With reference to FIG. 8A, an example further illustrating these datatypes and their interrelationships is shown for an implantable medicaldevice that is a responsive neurostimulation system for epilepsy. Forthis system the implantable medical device would be connected toelectrodes that are implanted in the brain that are used for deliveringelectrical stimulation to the brain to reduce seizures. In this case theimplantable medical device has been programmed to detect two patternspresent at seizure onset and to provide stimulation therapy for either.Referring to FIG. 8A, pattern B1 is a 40 Hz low-amplitude signal, andpattern B2 is an approximately 20 Hz higher amplitude signal.

The histogram data 704 (FIG. 7) for these events for a seven day periodare shown in FIG. 8B, where the y-axis amplitude represents the numberof events for each pattern that occurred within one hour bins. Note thatthese data do not indicate when the events occurred within the hour, nordo they indicate the relationships between subsequent events. These datado show that pattern B1 occurs more frequently and has daily periodswhere it is more frequent, whereas pattern B2 occurs relativelyinfrequently.

Detailed event sequence data 706 (FIG. 7) and waveform data 708 areshown for a common data sequence in FIG. 8C. The top panel shows thedetailed event sequence data 706 in time order of occurrence. These dataare very useful for devices that deliver stimulation therapy in sequencewhere each therapy may differ to assess the effectiveness of differenttherapies. These data may also provide insight into event durations. Thebottom panel of FIG. 8C shows the waveform data 708, which in this caseis electrocorticogram (ECOG) data. The waveform data 708 areparticularly useful for assessing the effectiveness of the detectionrelative to the observed pattern. In addition, waveform data 708 areuseful for monitoring electrode operation and can help diagnoseelectrode malfunctions which produce noise distinctly different fromnormal signals that a trained observer can easily detect.

The timelines covered by the types of memory 704, 706, 708 are shown inFIG. 9 for the situation where data transfer occurs at the present time,which is at the right side of the graph. Histogram data 902 covers afixed period of time, for example the past 10 days. Detailed eventsequence data 904 is continuous in nature, but the amount of timecovered prior to overwrite is variable and depends on patient activity.Waveform data events 906 a-906 d occur sporadically and are notcontinuous like the two aforementioned data types. In FIG. 9 theimplantable medical device is configured to store three waveform dataevents 906 and data transfer once again occurs at the present time. Thewaveform data events would be stored sequentially with 906 a beingstored first followed by 906 b and 906 c. However, when event 906 doccurs, the implantable medical device must either overwrite the oldestwaveform data 906 a or not record the latest waveform data event 906 d.In this example the shading of waveform data event 906 a indicates thatthe data event 906 a has been overwritten.

Peak Signal Strength Time Adaptation

To minimize RF power consumed by the implantable medical device duringdata retrieval, a patient should be as close to a data retrievalapparatus as possible for the period of time needed for data retrieval,which could be several minutes depending on the amount of data, thesystem design, the ambient background electromagnetic noise or otherfactors. One approach is to locate the data retrieval apparatus near thepatient's bed, possibly on a bedside stand, and then to perform the dataretrieval when the patient is asleep and thus likely to remain in thesame general area relative to the data retrieval apparatus. One way ofrealizing this goal is for the physician to ask the patient about theirsleep cycle and then to have a programmable data retrieval time settingin the data retrieval apparatus that results in data retrieval occurringat a fixed time based on the information the patient provides about whenhe or she usually is in bed and/or asleep. The disadvantages of thisapproach are that it requires additional effort by the physician, issubject to programming errors by the physician and sleep reportingerrors by the patient, and it is not robust relative to changes in thepatient's sleep cycle that may occur due to travel, time-zone changes,or lifestyle changes such as work or school schedule changes.

In accordance with techniques disclosed herein, an alternative approachinvolves ascertaining the patient's proximity to the data retrievalapparatus by briefly establishing RF telemetry during a calibrationperiod (and recalibration periods, if necessary) so that the dataretrieval apparatus can automatically adapt to the patient's likelysleep cycle.

With reference to FIG. 10, three possible conditions that might occurduring the course of the day are shown. Within the patient's bedroom1002, the data retrieval apparatus 1006 is located near the patient'sbed. In one situation 1004 the patient is in bed and the data retrievalapparatus 1006 is located a distance D1 away. In a second situation 1010the patient is sitting and the data retrieval apparatus 1006 is locateda distance D2 away, which is twice as distant as D1. In a thirdsituation 1008 the patient is in the room further away and the dataretrieval apparatus 1006 is located a distance D3 away, which is threetimes as distant as D1.

If the data retrieval apparatus 1006 establishes a telemetry link withthe implantable medical device, the RF electric field strength producedby the implantable medical device at the data retrieval apparatus 1006would be a function of the separation distance D1, D2, D3 and wouldcorrelate with the signal-to-noise measured by the data retrievalapparatus for a given noise environment. Exemplary signal-to-noisemeasurements corresponding to the three distances D1, D2, D3 are shownin FIG. 11.

As previously described, retrieving data from the implantable medicaldevice when the patient is in the closest proximity (such as when theyare in bed when the data retrieval apparatus is located very near to thebed), maximizes the signal-to-noise. This allows the highest data ratefor a given design and power level, and minimizes the battery energyused by the implantable medical device to transmit the data.

To determine when the patient is positioned so as to allow for a maximumsignal-to-noise, or an signal-to-noise above a threshold criterion, acalibration method may be used. During calibration the data retrievalapparatus 1006 opens a communications channel with the implantablemedical device to measure the signal-to-noise on the communicationschannel. The data retrieval apparatus 1006 does this in a periodic andsystematic manner. For example, calibration may occur by having the dataretrieval apparatus 1006 periodically (e.g., every 30-60 minutes) openthe communications channel very briefly with the implantable medicaldevice to assess the communications channel signal-to-noise. Theduration of the communications may be the minimum needed to measure thesignal-to-noise at that instant and hence may be short and accordingly,consume minimal battery energy.

Various methods for assessing the signal-to-noise of the communicationschannel can be implemented by one skilled such as examining a carrier ordemodulated signal voltage in an amplifier stage, or by monitoring thegain needed to amplify the signal to the appropriate level for thedetection circuit used for decoding. As previously described, thereceived signal strength indication could also be used as the metric forthis method.

The result of this process for a representative single day isillustrated in FIG. 12, which shows individual signal-to-noisemeasurements as sampled every 60 minutes over a 24 hour period beginningat 8:00. In this example the signal-to-noise measurements are at theirhighest values continuously for the samples between 21:00 and 05:00.This pattern of signal-to-noise measurements indicates a pattern ofclose proximity between the implantable medical device and the dataretrieval apparatus, suggestive of patient sleep between those times.

Because sleep patterns vary, and sample times may occur when a patientis momentarily absent from the bed over the course of the night formicturition or other reasons, a more robust approach would be to sampleover multiple days (e.g., 3-10 days). An exemplary result of thisprocess for a representative calibration period is shown in FIG. 13 intabular form, which includes the signal-to-noise measurements as sampledevery 60 minutes per day, over a seven day period. In this example, thesignal-to-noise has levels between 0 and 4. Different embodiments mayhave different signal-to-noise range resolutions, but the samecalibration principles would apply. The bottom line of the table in FIG.13 shows the average signal-to-noise measured for each hour (e.g.,02:00) over the 7 day calibration period.

The average signal-to-noise values shown in the table of FIG. 13 areplotted in FIG. 14. The values shown by the non-connected squares arethe average signal-to-noise values over seven days for that time period.For example, at 10:00 the signal-to-noise is zero, meaning the dataretrieval apparatus 1006 (FIG. 10) was unable to establish acommunications channel with the implantable medical device on any of theseven days during the calibration period. It will be beneficial totransfer data at a time when the patient is in very close proximity tothe data retrieval apparatus for the complete time needed to transferall data at the fastest possible data rate, such as when the patient isin bed sleeping. Sleep periods could be inferred for times when thesignal-to-noise is maximized for long periods, such as six to eighthours. To determine probable times when sleep occurs, it would bebeneficial to filter the signal-to-noise time plot. Many filteringmethods are implementable by one skilled in the art. In FIG. 14 arectangular (sinc) filter has been applied to create the smoothed lineplot. This filter uses 7 hours of data, which would tend to create asingle peak for a patient that slept a typical 7 hours per night. Theoperation of the filter applied in this example is describedmathematically below where SNR_(i) represents the averagesignal-to-noise for hour i (e.g., 02:00) over the entire 7 daycalibration period.SNR_(i)=(SNR_(i−3)+SNR_(i−2)+SNR_(i−1)+SNR_(i)+SNR_(i+1)+SNR_(i+2)+SNR_(i+3))/7  (Eq.2)

Various methods of optimizing the time for data retrieval areimplementable by one skilled in the art. One method is to set theretrieval time for peak of the smoothed, average signal-to-noise data asshown by the arrow 1500 in FIG. 15. Another method is to specify whatsignal-to-noise is acceptable and to determine what time represents themidpoint of contiguous values where the smoothed, averagesignal-to-noise values exceed that level. This is shown in FIG. 1600where the threshold level for an acceptable signal-to-noise is level 3,and the midpoint of the time when this is exceeded is shown by the arrow1600.

These methods for determining optimum data transfer times could betriggered to re-run after an unsuccessful retrieval attempt, or after aseries of unsuccessful interrogation attempts, to adjust to patientschanging sleep patterns. In addition, this method may incorporate astart-up phase where a single day or a multiple of days less than therequisite calibration period number of days (7 days in the priorexample) is used to schedule data retrieval time, in an albeit lessoptimized manner, prior to the elapse of the requisite calibrationperiod number of days.

With reference to FIG. 17, a process for calibrating the retrieval ofpatient data from an active implantable medical device is shown. Insummary, this process determines optimum times for data retrieval usingthe aforementioned calibration method that involves brief systematic andperiodic signal strength determination combined with averaging andsmoothing. Such a method maximizes the probability of data retrieval atthe highest possible bandwidth for a given communications channel designand power level, which minimizes the energy an implantable medicaldevice uses to transmit data and hence maximize battery longevity.

The process of FIG. 17 may be performed by a data retrieval apparatusconfigured to communicate with an active implantable medical device. Thedata retrieval apparatus obtains a number of measures over a firstperiod of time (step 1702). The measures correspond to a quality of acommunications channel between the data retrieval apparatus and theactive implantable medical device. Such quality measures may include,for example, one or more of a signal-to-noise, a received signalstrength indication, and packet error rate, or a combination thereof. Asdescribed above, the first period of time may range from 24 hours to anynumber of days, where the number of days may range from three days toten days.

The data retrieval apparatus then determines a trend in the plurality ofmeasures over the first period of time (step 1704). The trend may bedetermined by quantifying the obtained quality measures as a function oftime. For example, the data retrieval apparatus may collectsignal-to-noise measurements, and quantify those measurements as afunction of time over a one day period, such as described above withreference to FIG. 12. The data retrieval apparatus may also quantifysignal-to-noise measurements by determining, for each day within thefirst time period, signal-to-noise measurements for sub-time periods,e.g., hours, within the day. The data retrieval apparatus may thendetermine an average signal-to-noise for each sub-time period, over theentire time period. An example of quantifying measurements is thismanner is shown and described above with reference to FIG. 13. Aexemplary trend is represented by the data and fitted curve shown inFIG. 14.

The data retrieval apparatus determines at least one preferred timeduring which to retrieve data based on the trend (step 1706). To thisend, the data retrieval apparatus further processes the quantifiedquality measurements, such as the average signal-to-noise, to identify atime or time duration during which one or more of the measurementsindicate a higher quality of communication relative to other times ortime durations. For example, the data retrieval apparatus may identify atime of day, e.g. hour, at which the quality of communication is at apeak (see, e.g., FIG. 15). Alternatively, the data retrieval apparatusmay identify a time range, e.g., midnight to 4:00 am, during which thequality of communications satisfies a quality criterion. For example,the time range may correspond to a period of time during which thesignal-to-noise is above a threshold value (see e.g., FIG. 16).

Subsequent to the calibration, the data retrieval apparatus interrogatesthe active implantable medical device to retrieve data during thepreferred time (step 1708). Interrogation involves establishing acommunications link with the active implantable medical device, sendinga request for data to the medical device and receiving data from themedical device. The data retrieval apparatus monitors for unsuccessfulinterrogation attempts (step 1710). Such monitoring may involve the dataretrieval apparatus not receiving an acknowledgement from theimplantable medical device establishing a communication link.Alternatively, such monitoring may involve the data retrieval apparatusdetermining that a packet error rate in the communications link is belowa threshold requirement indicative of quality data reception. Theconsequence of tolerating a large number of failed attempts is increasedimplantable medical device battery usage. Accordingly, if a prerequisitenumber of interrogation attempts are unsuccessful, the data retrievalapparatus executes a recalibration process by repeating the obtaining ofa plurality of measures (step 1702), determining a trend (step 1704) anddetermining a preferred time (step 1706). The prerequisite number offailed attempts may be as little as one attempt, but may be programmableto a higher number based on performance of the RF communication linkbetween the active implantable medical device and data retrievalapparatus. In one configuration, the recalibration process isstreamlined relative to the initial calibration process in order toconserve power. To this end, during recalibration the data retrievalapparatus obtains quality measures over a time period that is less theprior period during which measures were obtained for the initialcalibration. If interrogation (step 1710) is successful the dataretrieval apparatus stops the process (step 1712).

Transmission Power Optimization Using Signal Strength Feedback

Based on the aforementioned methods for optimizing signal-to-noise, italso may be possible to lower the implantable medical device RF powerlevel without significantly impacting data transfer rates to result in anet energy savings. Shown again in FIG. 18 is the relationship forShannon's Channel Capacity Theorem, where the relationship betweensignal-to-noise quality measurements and communications link quality,e.g., channel capacity, are presented. A range of quality measurements,e.g., signal-to-noises, is identified as region “A.” A communicationslink between an active implantable medical device and data retrievalapparatus having an signal-to-noise within the range of region “A”provides the channel capacity necessary for effective transfer of databetween the devices. Using the methods previously described, a dataretrieval apparatus may be configured to initiate data transfer when theimplantable medical device is generally reliably in close proximity suchthat the signal-to-noise achieved is in region “A.”

With continued reference to FIG. 18, the slope of the curve withinregion “A” is substantially small. Accordingly, for device communicationoperating within region “A,” a change in RF power level has minimalimpact on communications quality. In other words, as the RF power levelof the implantable medical device is reduced and the signal-to-noiseaccordingly decreased, the impact on the channel capacity of acommunications link is less pronounced than in other regions of thecurve. For example, changes in RF power level in region “B” may have asevere impact on channel capacity.

Once the system has been optimized to operate in region “A” based onclose proximity between the implantable medical device and the dataretrieval apparatus, the data retrieval apparatus may feedback thesignal-to-noise (or received signal strength indication or packet errorrate) detected to the implantable medical device so that the implantablemedical device RF transmission power level may be adjusted downwarduntil the signal-to-noise reached a minimum threshold point “C.” Theminimum threshold represents a point below which channel capacity isinadequate to meet minimum data rate requirements.

With reference to FIG. 19, a process for adjusting the powertransmission of an active implantable medical device is shown. Insummary, the process provides for adjusting the active implantablemedical device transmission power to the lowest level that supports aminimum performance requirement, such as a threshold channel capacity. Ameasure of signal strength of a signal transmitted by the activeimplantable medical device is feedback to the implantable medical deviceso that the RF transmission power can be reduced to the lowest levelthat supports the required data rate. The process minimizes the energyan implantable medical device uses to transmit data and hence increasesbattery longevity.

The process of FIG. 19 may be performed by an active implantable medicaldevice configured to communicate with a data retrieval apparatus. Theimplantable medical device receives a measure of quality of a signaltransmitted by the implantable medical device (step 1902). The signaltransmitted by the implantable medical device may be sent to a dataretrieval apparatus, in which case, the measure received by theimplantable medical device is a feedback signal received from the dataretrieval apparatus. The measure of quality may be one of asignal-to-noise, a received signal strength indication, or a packeterror rate of the signal transmitted by the implantable medical device.

The active implantable medical device compares the measure to acriterion (step 1904). The criterion may be a minimum quality measure,below which a minimum performance requirement for communication may notbe obtained. For example, with reference to FIG. 18 described above, inone configuration the minimum quality measurement is a signal-to-noisebelow which channel capacity is inadequate to meet minimum data raterequirements. In FIG. 18, the minimum quality measurement is thesignal-to-noise corresponding to point “C”, and the minimum performancerequirement is the channel capacity corresponding to point “C”.

Next, the active implantable medical device determines if the measure isat or near the criterion (step 1906). The intent is to have theimplantable medical device reduce its transmission power to a level thatcauses the quality measure to closely approach the criterion withoutfalling below it. To this end, if the measure is not at or near thecriterion (step 1906), the implantable medical device adjusts, e.g.,reduces, the signal transmission power level (step 1908), and theprocess is repeated until the measure satisfies the minimum criterion.If the measure is at or near the criterion (step 1906) the implantablemedical device stops the process (step 1919). Alternatively, adjustingthe signal transmission power may include increasing the power level, ifthe communications quality measure falls below the threshold.

Interrogation Frequency Adaptation

It is important that data be retrieved prior to data overwrite so thatthe physician obtains a complete understanding of implantable medicaldevice performance. One way of realizing this goal is for the physicianto program a data retrieval interval (e.g., every day, every three days,every week) that is frequent enough to avoid overwrite. Thedisadvantages of this approach are that it requires additional effort bythe physician, is subject to programming errors by the physician, anddifferent types of data require interrogation at different intervals aspreviously described. Furthermore, the rate of events that theimplantable medical device stores in memory may vary with the patient'smedical condition, which results in variations in the time beforeoverwrite, and a fixed interval does not adjust to these variations.

An alternative to the fixed interval approach is to have the dataretrieval apparatus assess memory availability as data is retrieved andthen to schedule the next retrieval based on an estimate of whenoverwrite will occur.

With reference to FIG. 20, histogram data 2002 is fixed and may bescheduled for retrieval after an elapsed time of T_(H) that is apercentage of the total histogram data time coverage period. Thecoverage time period is a programmed value and thus may be known by thedata retrieval apparatus. For example, if the histogram data covers aten day period, the data retrieval apparatus may schedule data retrievalevery nine days to provide a safety margin in the event interrogation isunsuccessful on a given day.

Detailed event sequence data 2004 has variable time coverage aspreviously discussed with reference to FIG. 9. This data type includesevent type and time of occurrence and is presented in order ofoccurrence. Upon data retrieval, the data retrieval apparatus may assessthe past use of the memory portion allocated to this data type based onthe retrieved data and schedule the next detailed event sequence data2004 accordingly. For example, with reference to FIG. 20, the dataretrieval apparatus may schedule the next retrieval at time T_(D) thatis a percentage of the elapsed time that the detailed event sequencedata covers. In other words, the elapsed time may correspond to the timedifference between the oldest event and the most recent event. In theevent the data retrieval occurs prior to the detailed event sequencedata 2004 memory being full, the percentage of memory used relative tothe time coverage of that data may be used to estimate the time when thememory would have been full.

Waveform data 2006 b, 2006 c, 2006 d is episodic. An approach forscheduling when waveform data retrieval should next occur is to schedulethe next data retrieval to occur at a time interval equal to the timethat has elapsed since the oldest waveform data event 2006 c was stored.Referring to FIG. 20, if the implantable medical device can store threeevents, then waveform data 2006 b is the oldest waveform and the nextretrieval of waveform data may be scheduled based on the time of theoccurrence of the oldest waveform. For example, referring again to FIG.20, the time until the next retrieval would correspond to the elapsedtime between the present time and the time of occurrence of waveformdata 2006 b, which is time T_(W). Alternatively a safety margin could beapplied and an interval that is a percentage of T_(W) could be used(e.g., 90%×T_(W)). In the event that the memory allocated for waveformdata is not full, the next waveform data retrieval could be scheduled tooccur at longer time interval. For example, if the implantable medicaldevice were configured to store three waveform events and the lastwaveform data retrieval interval was set for 24 hours, but only onewaveform event were recorded, the retrieval interval could be increasedto a longer interval than the prior interval by a fixed amount (e.g., 24hours) or it could be increased based on the ratio of total availablememory to the used memory (24 hours×3 events÷1 event used). In additionto the above fixed time values, statistical methods could be applied sothat data retrieval intervals are scheduled at averages or medians ofthe times (T_(H), T_(W), T_(D)) measured on a plurality of occasions.

The data retrieval apparatus may incorporate programmable constraintsthat limit total data retrieval to avoid implantable medical devicebattery depletion. For example, data retrieval could be adaptable asdescribed herein, but could be limited to occur no more frequently thanevery N days or some other interval that is acceptable relative toimpact on battery longevity. Alternatively, the amount of data per unittime could be used as a constraint.

For example, 500 kilobytes per week (seven days) may be specified as aconstraint for data retrieval. Using the methods described herein thedata retrieval apparatus may determine that T_(W), the time betweenwaveform data retrieval, should be every day, however, after five daysthe amount of waveform data retrieved reaches 500 kilobytes, so theconstraints then apply and additional waveform data are not retrieved.In other words, the scheduled data retrievals are subordinate to thedata limit imposed by the data retrieval apparatus. After the period oftime associated with the data limit has expired, another allocation ofdata amount, e.g., 500 kilobytes, becomes available and data retrievalmay begin again according the schedule established by the data retrievalapparatus.

In this manner a precise limit on data transmitted can be applied, whichshould provide a predictable estimate of data transmission impact onimplantable medical device battery longevity. Using either of theaforementioned methods (minimum time between interrogations or specifiedmaximum amounts of data per time) do not preclude that the differentdata types described may have differing data limit constraints or thatsome data types may be unconstrained while others are constrained.

With reference to FIG. 21, a process for scheduling the retrieval ofdata from an active implantable medical device is shown. The process maybe performed by a data retrieval apparatus. The data retrieval apparatusretrieves different data types from an active implantable medical device(step 2102). Each data type may have portion of a memory of theimplantable medical device allocated to it, such as described above withreference to FIG. 7. The data types may include different types of data,such as those also described with reference to FIG. 7. In summary, afirst type may be histogram data collected over a known period of timethat includes a count of a number of occurrences of at least one type ofa physiological event over a period of time. A second type may be a timeand order of occurrence of each of a number of different physiologicalevents. The third type may be waveforms recordings of physiologicalevents.

The data retrieval apparatus schedules a next retrieval of the data type(step 2104) based on a known period of time or based on time dataincluded in retrieved data. For example, in the case of the first typeof data, the data retrieval apparatus calculates a percentage of theperiod of time during which histogram data is collected and schedulesthe next retrieval of this data type as a percentage of that period oftime. In the case of the second type of data, the data retrievalapparatus determines the elapsed time between the oldest occurrence ofsecond data type and the most recent occurrence of second data type andschedules the next retrieval based on the elapsed time. For example, thedata retrieval apparatus may set the time as a percentage of the elapsedtime. In the case of the third data type, the data retrieval apparatusdetermines the elapsed time between the most recent data retrieval andthe occurrence of the oldest waveform if all waveform allocations areused and schedules the next retrieval based on the elapsed time or apercentage thereof. Alternatively, if all waveform data memory is notused the next retrieval may be extended by a fixed or pro-rated amountbased on actual memory usage.

The data retrieval apparatus may set a limit on the amount of data to beretrieved during a period of time (step 2106). A limit and time periodmay be separately set for each of the types of data stored in theimplantable medical device. Prior to the next scheduled data retrieval,the data retrieval apparatus determines whether the limit on the data,or the type of data, for the current time period as been exceeded (step2108). If the limit has been exceeded, the data retrieval apparatusstops and refrains from retrieving data (step 2110). If the limit on thedata has not been exceeded, the data retrieval apparatus retrieves thedata, or data type, in accordance with the schedule (step 2112).

FIG. 22 is a diagram illustrating an example of a hardwareimplementation for a data retrieval apparatus 2206 employing aprocessing system 2210. The processing system 2210 may be implementedwith a bus architecture, represented generally by the bus 2224. The bus2224 may include any number of interconnecting buses and bridgesdepending on the specific application of the processing system 2210 andthe overall design constraints. The bus 2224 links together variouscircuits including one or more processors and/or hardware modules,represented by the processor 2212, a measurement module 2214, a trendmodule 2216, a scheduling module 2218, an interrogation/retrievingmodule 2220, and a computer-readable medium 2222. The bus 2224 may alsolink various other circuits such as timing sources, peripherals, voltageregulators, and power management circuits, which are well known in theart, and therefore, will not be described any further.

When functioning to implement the method of FIG. 17, the modules 2214,2216, 2218 and 2220 function as follows: The measurement module 2214obtains a plurality of measures over a period of time. The measurescorrespond to a quality of a communications channel between the dataretrieval apparatus and an active implantable medical device. The trendmodule 2216 determines a trend in the plurality of measures over theperiod of time. The scheduling module 2218 determines a preferred timeduring which to retrieve data based on the trend. Theinterrogation/retrieving module 2220 interrogates the implantablemedical device to retrieve data at or during the preferred time, andmonitors for unsuccessful interrogation attempts. If a prerequisitenumber of interrogation attempts are unsuccessful, the modules 2214,2216, 2218 and 2220 the obtain a new plurality of measures, determineanother trend and preferred time, based on the new measures.

When functioning to implement the method of FIG. 21, the modules 2214,2216, 2218 and 2220 function as follows: The interrogation/retrievingmodule 2220 retrieves different data types from an active implantablemedical device. Each data type has a portion of a memory of theimplantable medical device allocated to it. The scheduling module 2218schedules a next retrieval of each of the data types based on a knownperiod of time or based on time data included in retrieved data.

The modules 2214, 2216, 2218 and 2220 may be software modules running inthe processor 2212, resident/stored in the computer readable medium2222, one or more hardware modules coupled to the processor 2212, orsome combination thereof. The processing system 2210 may be coupled to atransceiver 2224. The transceiver 2224 is coupled to one or moreantennas 2226. The transceiver 2224 provides a means for communicatingwith various other apparatus over a transmission medium, including forexample an implantable medical device. The transceiver 2224 receives asignal from the one or more antennas 2226, extracts information from thereceived signal, and provides the extracted information to theprocessing system 2210. In addition, the transceiver 2224 receivesinformation from the processing system 2210 and based on the receivedinformation, generates a signal to be applied to the one or moreantennas 2226.

The processing system 2210 includes a processor 2212 coupled to acomputer-readable medium 2206. The processor 2212 is responsible forgeneral processing, including the execution of software stored on thecomputer-readable medium 2222. The software, when executed by theprocessor 2212, causes the processing system 2210 to perform the variousfunctions described supra for any particular module. Thecomputer-readable medium 2222 may also be used for storing data that ismanipulated by the processor 2212 when executing software.

FIG. 23 is a diagram illustrating an example of a hardwareimplementation for an active implantable medical device 2304 employing aprocessing system 2310. The processing system 2310 may be implementedwith a bus architecture, represented generally by the bus 2324. The bus2324 may include any number of interconnecting buses and bridgesdepending on the specific application of the processing system 2310 andthe overall design constraints. The bus 2324 links together variouscircuits including one or more processors and/or hardware modules,represented by the processor 2312, a receiving module 2314, a comparisonmodule 2316, a transmission power adjustment module 2318, and acomputer-readable medium 2322. The bus 2324 may also link various othercircuits such as timing sources, peripherals, voltage regulators, andpower management circuits, which are well known in the art, andtherefore, will not be described any further.

When functioning to implement the method of FIG. 19, the modules 2314,2316, and 2318 function as follows: The receiving module 2314 receives ameasure of quality of a signal transmitted by the active implantablemedical device. The measure is received from an external data retrievalapparatus that received the signal transmitted by the implantablemedical device. The comparison module 2316 compares the quality measureto a minimum criterion. The criterion corresponds to a minimum qualitymeasure, which in turn, corresponds to a minimum performance requirementfor a communication channel between the implantable medical device andthe data retrieval apparatus. The minimum performance requirement may bea data rate, and the measure of quality may be one of a signal-to-noise,a received signal strength indication, and a packet error rate. Thetransmission power adjustment module 2318 adjusts a signal transmissionpower level until the measure is at or near the criterion.

The modules 2314, 2316 and 2318 may be software modules running in theprocessor 2312, resident/stored in the computer readable medium 2322,one or more hardware modules coupled to the processor 2312, or somecombination thereof. The processing system 2310 may be coupled to atransceiver 2324. The transceiver 2324 is coupled to one or moreantennas 2326. The transceiver 2324 provides a means for communicatingwith various other apparatus over a transmission medium, including forexample an implantable medical device. The transceiver 2324 receives asignal from the one or more antennas 2326, extracts information from thereceived signal, and provides the extracted information to theprocessing system 2310. In addition, the transceiver 2324 receivesinformation from the processing system 2310 and based on the receivedinformation, generates a signal to be applied to the one or moreantennas 2326.

The processing system 2310 includes a processor 2312 coupled to acomputer-readable medium 2306. The processor 2312 is responsible forgeneral processing, including the execution of software stored on thecomputer-readable medium 2322. The software, when executed by theprocessor 2312, causes the processing system 2310 to perform the variousfunctions described supra for any particular module. Thecomputer-readable medium 2322 may also be used for storing data that ismanipulated by the processor 2312 when executing software.

The various aspects of this disclosure are provided to enable one ofordinary skill in the art to practice the present invention. Variousmodifications to exemplary embodiments presented throughout thisdisclosure will be readily apparent to those skilled in the art, and theconcepts disclosed herein may be extended to other magnetic storagedevices. Thus, the claims are not intended to be limited to the variousaspects of this disclosure, but are to be accorded the full scopeconsistent with the language of the claims. All structural andfunctional equivalents to the various components of the exemplaryembodiments described throughout this disclosure that are known or latercome to be known to those of ordinary skill in the art are expresslyincorporated herein by reference and are intended to be encompassed bythe claims. Moreover, nothing disclosed herein is intended to bededicated to the public regardless of whether such disclosure isexplicitly recited in the claims. No claim element is to be construedunder the provisions of 35 U.S.C. §112, sixth paragraph, unless theelement is expressly recited using the phrase “means for” or, in thecase of a method claim, the element is recited using the phrase “stepfor.”

What is claimed is:
 1. A method of data retrieval by an external dataretrieval apparatus, said method comprising: obtaining a plurality ofmeasures over a period of time, the measures corresponding to a qualityof a communications channel between the data retrieval apparatus and anactive implantable medical device; determining a trend in the quality ofthe communication channel based on the plurality of measures obtainedover the period of time; determining a preferred time during which toretrieve data over the communication channel based on the trend in thequality of the communication channel; and wherein determining thepreferred time comprises processing the plurality of measures toidentify a time or time duration during which one or more of theplurality of measures indicate a higher measure of a quality ofcommunication relative to one or more of the plurality of measuresobtained during other times or time durations.
 2. The method of claim 1,wherein the plurality of measures comprises one or more of asignal-to-noise ratio, a received signal strength indication, and apacket error rate, or a combination thereof.
 3. The method of claim 1,wherein the period of time ranges from 24 hours to a plurality of days.4. The method of claim 1, wherein determining a trend comprisesquantifying the plurality of measures as a function of sub-time periodswithin the time period.
 5. The method of claim 1, wherein the preferredtime corresponds to the time at which the quality of communication is ata peak.
 6. The method of claim 1, wherein the preferred time correspondsto a time range during which the quality of communication satisfies aquality criterion.
 7. The method of claim 1, further comprising:interrogating the active implantable medical device to retrieve data ator during the preferred time; monitoring for unsuccessful interrogationattempts; and obtaining a new plurality of measures, determining a newtrend and determining a new preferred time, if a prerequisite number ofinterrogation attempts are unsuccessful.
 8. The method of claim 7,wherein obtaining the new plurality of measures is performed over aperiod of time less than the prior period of time during which theplurality of measures were obtained.
 9. An external data retrievalapparatus, comprising: a transceiver; and a processing system coupled tothe transceiver and configured to: obtain a plurality of measures over aperiod of time, the measures corresponding to a quality of acommunications channel between the data retrieval apparatus and anactive implantable medical device; determine a trend in the quality ofthe communication channel based on the plurality of measures obtainedover the period of time; determine a preferred time during which toretrieve data over the communication channel based on the trend in thequality of the communication channel; and wherein to determine thepreferred time, the processing system is further configured to processthe plurality of measures to identify a time or time duration duringwhich one or more of the plurality of measures indicate a higher measureof a quality of communication relative to one or more of the pluralityof measures obtained during other times or time durations.
 10. Theapparatus of claim 9, wherein the plurality of measures comprises one ormore of a signal-to-noise ratio, a received signal strength indication,and a packet error rate, or a combination thereof.
 11. The apparatus ofclaim 9, wherein the period of time ranges from 24 hours to a pluralityof days.
 12. The apparatus of claim 9, wherein to determine a trend, theprocessing system is further configured to quantify the plurality ofmeasures as a function of sub-time periods within the time period. 13.The apparatus of claim 9, wherein the preferred time corresponds to thetime at which the quality of communication is at a peak.
 14. Theapparatus of claim 9, wherein the preferred time corresponds to a timerange during which the quality of communication satisfies a qualitycriterion.
 15. The apparatus of claim 9, wherein the processing systemis further configured to: interrogate the active implantable medicaldevice to retrieve data at or during the preferred time; monitor forunsuccessful interrogation attempts; and obtain a new plurality ofmeasures, determine a new trend and determine a new preferred time, if aprerequisite number of interrogation attempts are unsuccessful.
 16. Theapparatus of claim 15, wherein the processor is configured to obtain thenew plurality of measures over a period of time less than the priorperiod of time during which the plurality of measures were obtained.